Acoustical echo canceller with sub-band filtering

ABSTRACT

The echo canceller is designed to be placed between a hands-free acoustical interface and a communications network. It comprises a plurality of processing paths connected in parallel and each allocated to one of a plurality of adjacent sub-bands taken from the spectrum band of the output signal. Each path comprises an analysis filter receiving the echo-containing signal for transmission after correction, a second analysis filter receiving the incoming signal coming from the network, and feeding an adaptive filter that supplies an estimated echo in the respective sub-band to the subtractive input of the subtracter and a synthesis filter. The adaptive filters in at least some of the sub-bands implement a QR decomposition RLS algorithm on the incoming signal, using the fast version thereof, with or without recursive order.

BACKGROUND OF THE INVENTION

The present invention relates to echo cancellers for use in telephoneinstallations. A major application lies in installations likely toinclude portable terminals or "hands-free" terminals. Such installationsinclude, in particular, digital cellular radiotelephone systems,videophone terminals operating in narrow band (8 kHz) or in enlargedband (16 kHz), and terminals for the conventional wire network.

The principle of an echo canceller is illustrated in FIG. 1 of thepresent application. FIG. 1 shows a "near" terminal which may be ateleconferencing set, a "hands-free" telephone handset, etc. The signalx travelling over a receive line LR and coming from a remote terminal 8is amplified by an amplifier 10 and then broadcast by a loudspeaker 12.The soundwaves coming from the loudspeaker 12 are transmitted byacoustical coupling (represented by path 13) to one or more microphones14 that are intended for picking up speech of a near speaker. Themicrophone 14 is connected to an amplifier 16 and the output signal z istransmitted over a send line LE to the remote terminal. The "remote"speaker placed at the remote terminal 8 will consequently hear not onlyany intended speech, but also an echo of his or her own speech after adelay due to the transmission time via the channels LE and LR, anddisturbed by the transfer function of the acoustical path 13.

The echo canceller includes an adaptive filter FA which receives theinput signal x and whose output is applied to the subtractive input of asubtracter 18 whose additive input receives the output from theamplifier 16. The coefficients of the filter FA are automaticallyadapted responsive to the error signal e sent over the send line LE andequal to the difference between the signal z (constituted by the echowhen there is no useful signal) and the output from the filter. When thespeaker at the near terminal is not speaking, the error signal isconstituted merely by residual echo. Often the echo canceller isprovided with a detector for detecting the presence of near speakerspeech, referred to as a double speech detector (DIP), which stops orslows down adaptation of the filter FA while the local speaker isspeaking, so as to prevent the filter from being disturbed by localspeech.

In general, the filters of echo cancellers in telephone installationsare digital adaptive transversal filters using a simple algorithm suchas the gradient algorithm or more commonly the normalized stochasticgradient algorithm, referred to as NLMS.

A major problem in implementing an echo canceller is due to the largenumber of coefficients required for taking account of the length of theimpulse response of the path 13 throughout the telephone band. Severalthousands of coefficients are required at the usual sampling frequencyof 8 kHz (narrow band) or of 16 kHz (enlarged band). To keep the volumeof computation compatible with the computation power of availabledigital signal processors, proposals have been made to subdivide thepassband in which echo cancelling is to be performed into a plurality ofsub-bands, each processed by a path having a sub-band analysis filter, acanceller allocated to the sub-band, and a sub-band synthesis filter.

This approach encounters difficulties. Either the filters are designedso that the sub-bands are separate, thereby avoiding spectrum aliasingeffects in each sub-band, but causing gaps in the spectrum of the signalas reconstructed by combining the outputs of the synthesis filterbank.Or else, a sub-band-feeding sub-sampling frequency is adopted which isgreater than the critical frequency for sub-sampling or decimation inorder to form guard bands which avoid spectrum aliasing, but thatconsiderably increases the computation speed required. Or else thesub-bands are allowed to overlap and account is taken of thecontribution of adjacent sub-bands in the path allocated to any onesub-band. This solution (U.S. Pat. No. 4,956,838) gives results that aresatisfactory, but it suffers from the drawback of considerablycomplicating the structure of an echo canceller.

It is also known that the algorithms conventionally used in echocancellers, and in particular the stochastic gradient algorithm, allowssignificant residual echo to remain in a noisy environment.

A certain number of filtering algorithms are known that make itpossible, in theory, to reduce the residual error. In particular, therecursive least squares algorithm or RLS algorithm is known which givesbetter performance than the NLMS algorithm commonly used in echocancelling. However it suffers from the drawback of being complex and ofhaving zones of instability. That is why it has not been used inacoustical echo cancellers, in particular because the complexity ofimplementing it would require a large amount of hardware and computationtimes that are incompatible with the delays that are acceptable intelephone communications. For example, in the European GSM standard fordigital cellular telephony, the maximum processing time allowed to astation is 0.1 s.

SUMMARY OF THE INVENTION

It is an object of the invention to provide an echo that makes itpossible to reduce the error e to a value that is very small, whilenevertheless retaining acceptable complexity and processing time.

To do this, it has been necessary firstly to make a certain number ofobservations.

The first observation is that it is possible to reduce the complexity ofcomputation quite considerably by combining the use of sub-bandprocessing with a fast version of the QR decomposition least squaresalgorithm, which has particularly satisfactory digital properties(robustness with finite precision, stability), while maintaining theeffectiveness of the least squares algorithm, with each sub-band beingfed by under-sampling. This advantage is particularly clear if analgorithm is used that is recursive on order. The second observation isthat the effectiveness of the QR algorithm is such that the contributionof the sub-bands on either side becomes negligible, even when the bandsoverlap in part, thereby avoiding the presence of gaps in thereconstructed spectrum but without needing the complexity required forfilters that take account of the contribution from the sub-bands oneither side.

Consequently, the present invention proposes an echo canceller designedfor use between a hands-free acoustical interface and atelecommunications network, the canceller comprising a plurality ofprocessing paths connected in parallel and each allocated to one out ofa plurality of adjacent sub-bands in the spectrum band of the outputsignal, each path comprising a sub-band analysis filter receiving theecho-containing signal that is to be delivered after echo correction, asecond sub-band analysis filter receiving the incoming signal andfeeding an adaptive filter implementing a fast version of a leastsquares algorithm based on the QR decomposition of incoming signal,which is recursive on order (commonly called "fast QR-LSL") ornon-recursive on order (commonly called "fast QR-RLS") and providing anestimated echo in the respective sub-band to the subtractive input ofthe subtracter, and a sub-band synthesis filter. Any solution ofintermediate order is also possible. The network may, in particular, bea GSM network, an RTC network, etc.

Very often, the echo phenomenon is not of the same magnitude in all ofthe sub-bands. For example, in some installations, the echo phenomenonis much more intense and must be corrected much more completely in lowfrequency sub-bands or in mid frequency sub-bands. Under suchcircumstances, it is possible to use filters implement the QRdecomposition least squares algorithm in those sub-bands which are mostaffected by echo, while the filters allocated to the other sub-bands canimplementing a simpler algorithm, e.g. the stochastic gradient algorithmNLMS, or even the sign algorithm.

In practice, the telephone band is subdivided into a number of sub-bandslying in the range four to eight for narrow band signals (8 kHz) andfour to sixteen for signals in enlarged band (16 kHz). Above eight, thesub-sampling rates achieved are too small compared with the common fullband sampling rates for 8 kHz and 16 kHz (narrow band and enlargedband). In addition, the additional improvement that can be expected doesnot justify the increased complexity. The total length of the filters(number of taps or order of the filters) generally lies in the range 64to 300 for a hands-free terminal placed in a vehicle and between 256 and512 for a hands-free terminal placed in a room, when dealing with narrowband signals. For enlarged band signals (16 kHz), these orders ofmagnitude are generally doubled.

It has been observed that beyond these values, the reduction that can behoped for decreases only very slowly, unless filters are used that arethree or four times longer.

The invention will be better understood on reading the followingdescription of particular embodiments given as non-limiting examples.The description refers to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1, already mentioned, shows the principles on which an echocanceller is based; and

FIG. 2 is a block diagram showing one possible structure for an echocanceller of the invention.

DETAILED DESCRIPTION

Before describing the invention, information about echo cancellers asused in telephony and the notation that will be used will be summarized.The following notation is used:

x(n): incoming signal at instant t_(n) (sample n)

z(n): echo

e(n): residual signal at instant n, assuming that there is no localspeech (residual error)

h: transverse filter of the echo canceller

X_(n+1),N (n): the matrix (n+1) rows and N columns matrix at instant nof the form: ##EQU1## Z_(n+1),1 (n): the echo matrix at instant n, ofthe form: ##EQU2## where λ is a forgetting factor E_(n+1),n (n): thecolumn matrix of the residual signals: e(0), . . . , e(n).

Using the conventional least squares algorithm, referred to as the RLSalgorithm, and in the absence of local speech, attempts are made tominimize the output variance estimator: ##EQU3## which can be written inthe following form, using matrix notation:

    E.sub.n+1,n (n)=Z.sub.n+1,1 (n)-X.sub.n+1,N (n).H

As mentioned above, the invention makes use of a QR type decompositionof the input signal, implementing an orthogonal transformation matrix Q(i.e. in which the product when multiplied by its transpose is equal tothe identity matrix), having n+1 rows and n+1 columns, making itpossible to obtain a higher triangular matrix R(n) having N rows and Ncolumns, by applying the following relationship at instant n: ##EQU4##

This transformation makes it possible to adapt the filter by a processof continuously updating the QR decomposition.

Minimization in the least squares sense is performed by applying the QRtransformation to equation (1); calculation shows that the orthogonalmatrix Q satisfies the following updating relationship: ##EQU5##

It can be seen that it is possible to obtain the matrix Q(n) from theestimated preceding transform matrix Q(n-1) and a set of N Givens'rotations enabling the last line of the input signal matrix to beeliminated: ##EQU6## where Q(n) designates the product of N consecutiveGivens' rotations:

    Q.sub.n+1,n+1 (n)=QΘ.sub.N-1 . . . QΘ.sub.Q

The rotation Θ_(i) serves to eliminate sample x(n-i) in the matrix:##STR1##

Finally, by retaining only the rows and columns that relate to Nrotations, an updating formula is reached that defines the orthogonaltransform matrix QΘ_(N+1),N+1 : ##EQU7## It is possible to evaluate thea posteriori residual error e(n) which is the last term of vector E:

    e(n)=E.sup.t.sub.n+1,1 (n) O, . . . , 0, 1!.sup.1

which can also be written as follows, using E_(q) to designate thevector that results from the orthogonal transform of E by Q:

    e(n)=Eq.sup.t.sub.n+1,1 (n).Q.sub.n+1,1 (n) O, . . . , 0, 1!.sup.t

It can be shown that e(n) is equivalent to:

    e(n)=e.sub.q (n)γN-1(n)0

where e_(q) (n) is the last term of E_(q) (n)

γ_(N-1) is equal to: ##EQU8## Θ being the normalized Givens' rotationangle.

Computing the a priori residual error in turn leads to evaluating it asε(n)=eq(n)/γ(n) when γ is the square root of the likelihood variable.

    λ.sup.2 (n)=e(n)/ε(n)

An estimate of the last term eq(n) of the error vector after rotationcould be the geometric mean of the a priori and a posteriori errors.

Proposals have already been made to implement a fast QR-RLS algorithm infields other than acoustical echo cancelling, so it is not described indetail. Reference may be made on this respect to articles such as:

Ling, "Givens' rotation based least squares lattice and relatedalgorithms", IEEE Trans. on Signal Processing, Vol. 39, No. 7, July1991.

Regalia et al., "On the duality between fast QR methods and latticemethods in least squares adaptive filtering", IEEE Trans. on ASSP, Vol.39, No. 4, pages 879-891, April 1991.

B. Yang, J. F. Bohme, "Rotation based RLS algorithms: unifiedderivations, numerical properties, and parallel implementations", IEEETrans. on Signal Processing, Vol. 40, No. 5, May 1992.

The "fast" algorithms reduce the complexity of filters which is normallyof the form O(N²) where N is the order of the adaptive filter, reducingit approximately to O(N).

On this topic, it may also be useful to provide information on theevolution of the algorithm from complexity in O(N²) to complexity inO(N).

The direct QR decomposition applies to the Cholesky factor of theself-correlation matrix, whereas the inverse decomposition is applied tothe inverse of the Cholesky factor. This distinction is the startingpoint for two families of least squares algorithms based on the QRdecomposition.

The corresponding initial algorithms are in O(N²), and they are calledrespectively QR-RLS and IQR-RLS.

For each of those two families there exist fast versions in O(N), eitherof fixed order or else recursive on order.

In the context of direct QR decomposition, mention may be made of theCioffi algorithm which is of the FQR-RLS (fast QR-RLS) type of fixedorder, and of the Regalia & Bellanger algorithm of the FQR-LSL (fast QRleast square lattice) type of recursive order described in the abovearticle.

For inverse QR decomposition, a derivation for each case (fixed orderand recursive order) can be found in Theodoridis (ICASSP-95).

There also exists an algorithm based on QR methods but using theHouseholder transform instead of fast version direct QR type Givens'rotations, but which differs from the other algorithms mentioned aboveby the fact that it identifies the transverse filter. Such an algorithmis described by Liu in an article published in IEEE Trans. on SP, March1995.

Consequently, a description will be given of examples of distribution ofthe functional blocks required for implementing particular embodiments.

The echo canceller shown diagrammatically in FIG. 2 makes use of a foursub-band division into four sub-bands. Elements corresponding toelements of FIG. 1 are designated by the same reference numbers. It isassumed below that the canceller is for use in a hands-free telephoneinstallation designed to operate in the band extending from 300 Hz to3.4 kHz, with sampling at 8 kHz, it being understood that such a methodcan be used with hands-free terminals with enlarged bandwidth (16 kHz),and with processing being performed in other numbers of sub-bands.

The canceller comprises an input analog-to-digital converter 22 whichfeeds two parallel-connected filters 24 and 26. The filter 24 is ahighpass or bandpass filter, e.g. having a low cutoff frequency of about2 kHz. The filter 26 is a lowpass filter, having substantially the samecutoff frequency, so as to avoid overlap between bands. Each of thefilters 24 and 26 is followed by a sub-sampling circuit 28 designed toperform decimation with a ratio of 2 and to direct the samples to eachof two sub-band analysis filters. Thus, using filters 30a, 30b, 30c, and30d, four sub-bands are thus constituted which extend, for example,respectively up to 1 kHz, from 1 kHz to 2 kHz, from 2 kHz to 3 kHz, andfrom 3 kHz to 4 kHz.

The filters 30 may be of conventional type. In particular, it ispossible to use conjugate quadrature filters (CQF), or quadrature mirrorfilters (QMF), and infinite impulse response filters (IIR). It is alsopossible to use wavelet decomposition filters (WDF) which enable a finerdivision to be obtained.

Each of the filters 30 is followed by a sub-sampler 32 and by asubtracter 34 which receives the output from a respective cancellingfilter 36a, 36b, 36c, or 36d.

To carry out analysis and synthesis of the signal in sub-bands, it ispossible to use sub-band decomposition and recomposition schemes otherthan binary tree recomposition as described above. For example, it ispossible to select decomposition by means of banks of filters that mayor may not be modulated or uniform, and which do not restrict the choiceof structure for decomposition into sub-bands.

As mentioned above, it is often advantageous to perform QR-RLS typefiltering in the lower band only, i.e. in the sub-bands fed by thefilters 30a and 30b. In contrast, the filters 36c and 36d (higher band)can implement a normalized LMS algorithm which requires much lesscomputation power. The QR decomposition least squares algorithm may beimplemented only in the two middle sub-bands.

More generally, it is possible to use the QR decomposition least squaresalgorithm for the adaptive filters of sub-bands having high input signalenergy and a less complex algorithm (e.g. NLMS) in the sub-bands havinglower energy. Choices can be made after prior analysis of the inputsignal mean energy levels in each of the sub-bands in the type ofdecomposition under consideration.

The subtracters 34 feed a synthesis circuit 38 that is symmetrical tothe analysis circuits. In the example shown, it comprises over-samplers40 operating by adding zeros and interpolating, bandpass filters 24,adders 44, another bank of over-samplers 46, two output filters 48, andan adder 50 providing e(n).

The adaptive filters 36a to 36d which feed the subtractive inputs of thesubtracters 34 receive the signal x(n) distributed into sub-bands by twosuccessive banks of filter 52 and 54 and two banks of sub-samplers 56and 58 having the same characteristics as the filters and sub-samplersused for analysis z(n). The total number of adaptive filter taps, i.e.the order of the filters, generally lies in the range 64 to 256, whichlarger number has been found to be sufficient even in a teleconferenceinstallation in a room of large size, having long reverberation times,providing a sufficient level of sub-band decomposition is used in thatcase. The distribution of coefficients between the various sub-bandswill generally be equal, insofar as all of the sub-bands implement thesame algorithm. In contrast, the greater complexity of the QR-RLSalgorithm can lead to unequal distribution between the sub-bands usingthat algorithm and the sub-bands using an algorithm that requires lesscomplex computation. For example, if the canceller subdivides into foursub-bands, two of which use the QR decomposition least squaresalgorithm, then sixteen coefficients may be allocated to each of thosesub-bands and thirty-two coefficients to the other two sub-bands. Thisbrings the computation times for the various adaptive filters closertogether. In general, implementation can thus be performed byimplementing the adaptive filters on signal processors that are nowavailable on the components market.

The forgetting factor of the QR decomposition least squares algorithmwhich is involved in the recursive computation can be given a fixedvalue. In practice, it is necessary for the forgetting factor to begreater than (n-1)/n where n is the number of coefficients in the filterunder consideration.

Unlike fast transversal RLS algorithms where the value of the forgettingfactor must be large enough for avoiding divergence, QR decompositionleast squares algorithms (whether fast version or not) make it possibleto use a much more flexible adjustment range for the forgetting factorwithout any risk of divergence or of instability.

Consequently, it is preferable to provide the filters with adaptationmeans 60 for adapting the forgetting factor. In FIG. 2, such means 60are only shown for the adaptive filters 36a and 36b. The adaptationmeans may be generalized to the filters 36c and 36d implementing theNLMS algorithm, where similar control of the adaptation step size may benecessary or preferable.

A strategy which is generally advantageous consists in giving λ a valuethat is initially as small as possible so as to accelerate convergence,i.e. a value that is slightly greater than (n-1)/n=15/16=0.93 in thecase considered above. The means 60 may be designed to be controlled bya double speech detector and a room noise detector that are responsive,for example, to a level of signal z(n) as compared to the level ofsignal x(n) being greater than a given threshold. By adopting a valueclose to 1 for λ when double speech is detected, it is possible toreduce disturbances in the adaptation due to the local speaker, giventhe remanence that introduces.

Yet another strategy for choosing λ consists in storing, in the means 60a relationship for selecting λ over a few values from (n-1)/n to a valueclose to 1, e.g. as a function of the energy of the signal.

The means 60 used for adjusting the parameters of the QR decompositionleast squares algorithm, such as the forgetting factor λ and the orderof the filter, can be based either on simple principles of energycriteria, or else on spectral distortion computations which may beparametric or otherwise (e.g. the Itakura distance, cepstral distancesbetween the incoming signal paths taken at the outputs of 58 (a, b, c,and d) and the outgoing signal paths of 32 (a, b, c, and d)respectively). The means 60 may also be used for adjusting theadaptation step size of the NLMS algorithm.

It has been found that increasing the number of taps does not give riseto a significant improvement in echo cancelling unless the number oftaps exceeds about 1000 which gives rise to computation complexity andsampling rates that are excessive.

Advantageously, the filters that implement the NLMS algorithm in some ofthe sub-bands include means for adjusting the adaptation step size orthe convergence step size.

Means, not shown, may also be used to adjust the order of the filterautomatically in each sub-band as a function of the energy of the inputsignal x(n) in each sub-band so as to ensure greater robustness in thepresence of double speech and in the presence of noise. A strategy forselecting filter order is as follows: for a signal of zero energy in asub-band, the adjustment means reduce the order of the filter to zero.When the signal exceeds a threshold, corresponding practically to themaximum energy envisaged in the sub-band, the adjusting means give thecorresponding filter a maximum order. At intermediate energies, filterorder can be adjusted in a plurality of successive steps, e.g.simulating an exponential relationship similar to that of the acousticalimpulse response.

The invention can achieve effectiveness, as measured under theconditions laid down by the ERLE (echo return loss enhancement) standardof about 30 dB for 256 taps. Doubling the number of taps does notprovide significant improvement.

The invention is not limited to the particular embodiment described byway of example. In particular, the number of sub-bands could bedifferent, even though as a general rule it is pointless to have morethan sixteen sub-bands for narrow bandwidth or thirty-two sub-bands forenlarged bandwidth. It is also possible to use different algorithms witha distribution different from that given above.

We claim:
 1. An echo canceller for use between a hands-free acousticalinterface having a local source and loudspeaker means and acommunication network, for cancelling an acoustical echo due toacoustical coupling between said local source and said loudspeakermeans, comprising a plurality of processing paths connected in parallelrelation and each allocated to one of a plurality of mutually adjacentfrequency sub-bands of a frequency spectrum band of a signal originatingfrom said local source and to be delivered to the communication network,wherein each of said path comprises:a first analysis filter connected toreceive an echo-containing signal originating from said local source, tobe transmitted to said communication network after echo correction, asecond analysis filter connected to receive an incoming signaloriginating from the communication network and directed to saidloudspeaker means, an adaptive filter connected to receive an output ofsaid second analysis filter and constructed to supply an estimated echoin the respective one of said sub-bands as defined by the respectivefirst analysis filter and the respective second analysis filter, and asubtractor having an input connected to receive the echo containingsignal in the respective sub-band and a subtractive input connected toreceive said estimated echo in the respective sub-band, said echocanceller further comprising:a synthesis filter connected to receiveoutputs of all said subtractors, wherein said adaptive filters in thoseof the sub-bands having maximum incoming signal energy are arranged tocarry out a fast version QR decomposition least squares algorithm on theincoming signal, while the adaptive filters of the other sub-bandsimplement a different algorithm.
 2. An echo canceller according to claim1, wherein those of the adaptive filters which are assigned to the midsub-bands implement said QR decomposition algorithm, the other adaptivefilters implementing the normalized least squares algorithm or thenormalized stochastic gradient algorithm.
 3. An echo canceller accordingto claim 1, wherein said QR decomposition least squares algorithm isrecursive on order.
 4. An echo canceller according to claim 1, whereinsaid QR decomposition least squares algorithm is non-recursive on order.5. An echo canceller according to claim 1, wherein those of saidadaptive filters which are assigned to low frequency sub-bands implementsaid QR decomposition algorithm while the other adaptive filtersimplement the normalized stochastic gradient NLMS algorithm.
 6. An echocanceller for use between a hands-free acoustical interface having alocal source and loudspeaker means and a communication network, forcancelling an acoustical echo due to acoustical coupling between saidlocal source and said loudspeaker means, comprising a plurality ofprocessing paths connected in parallel relation and each allocated toone of a plurality of mutually adjacent frequency sub-bands of afrequency spectrum band of a signal originating from said local sourceand to be delivered to the communication network, wherein each of saidpath comprises:a first analysis filter connected to receive anecho-containing signal originating from said local source, to betransmitted to said communication network after echo correction, asecond analysis filter connected to receive an incoming signaloriginating from the communication network and directed to saidloudspeaker means, an adaptive filter connected to receive an output ofsaid second analysis filter and constructed to supply an estimated echoin the respective one of said sub-bands as defined by the respectivefirst analysis filter and the respective second analysis filter, and asubtractor having an input connected to receive the echo containingsignal in the respective sub-band and a subtractive input connected toreceive said estimated echo in the respective input connected to receivesaid estimated echo in the respective sub-band, said echo cancellerfurther comprising:a synthesis filter connected to receive outputs ofall said subtractors, wherein said adaptive filters in those of thesub-bands having maximum incoming signal energy are arranged to carryout a fast version QR decomposition least squares algorithm on theincoming signal and are provided with means for varying a forgettingfactor between a maximum value in the presence of high acoustical noiseor double speech, and a smaller value in the presence of single speech,while said adaptive filters in sub-bands other than those having maximumincoming signal energy implement a different algorithm.
 7. A cancelleraccording to claim 6, characterized in that said means are provided forvarying the forgetting factor between a minimum initial value that isgreater than (n-1)/n where n is the number of filter taps, and a maximumvalue close to 1, in the event of double speech being detected.
 8. Anecho canceller for use between a hands-free acoustical interface havinga local source and loudspeaker means and a communication network forcancelling an acoustical echo due to acoustical coupling between saidlocal source and said loudspeaker means, comprising a plurality ofprocessing paths connected in parallel relation and each allocated toone of a plurality of mutually adjacent frequency sub-bands of afrequency spectrum band of a signal originating from said local sourceand to be delivered to the communication network, wherein each of saidpath comprises:a first analysis filter connected to receive anecho-containing signal originating from said local source, to betransmitted to said communication network after echo correction, asecond analysis filter connected to receive an incoming signaloriginating from the communication network and directed to saidloudspeaker means, an adaptive filter connected to receive an output ofsaid second analysis filter and constructed to supply an estimated echoin the respective one of said sub-bands as defined by the respectivefirst analysis filter and the respective second analysis filter, and asubtractor having an input connected to receive the echo containingsignal in the respective sub-band and a subtractive input connected toreceive said estimated echo in the respective sub-band, said echocanceller further comprising:a synthesis filter connected to receiveoutputs of all said subtractors, wherein said adaptive filters in thoseof the sub-bands having maximum incoming signal energy are arranged tocarry out a fast version QR decomposition least squares algorithm on theincoming signal and are provided with means for automatically adjustingthe order of recursive filters on the order of the sub-bands as anincrease in function of energy in the signal x(n) input to eachsub-band.
 9. An echo canceller according to claim 8, characterized inthat said means for automatically adjusting the order of the filtersreduces the order of the filter of a sub-band to zero when the energy ofthe incoming signal is zero in said sub-band, and sets the order offilters to a maximum value when the incoming signal exceeds apredetermined value, with the order of the filter at intermediateenergies being adjusted by successive steps in application of a meanexponential relationship similar to that of the acoustical impulseresponse.
 10. An echo canceller according to claim 8, wherein saidadaptive filters in sub-bands other than those having maximum incomingsignal energy implement an algorithm different from the fast version QRdecomposition least squares algorithm.